Dear colleagues, and thank you Jean for provoking this.
Please bear with me while I bring a drop of academic content to the discussion, hoping we can expand it a bit.
What are mixed methods after all? I think the quanti x quali debate is quite reductionist; and honestly after all these decades I cannot believe we are still discussing if RCTs are the gold standard.
I would like to bring an approach that called my attention, which was presented by Professor Paul Shaffer from Trent University (Canada). His approach is focused mixed methods for impact assessment – but I understand it can be extrapolated to other types of studies – such as outcome assessment. What I like about his proposal is that it goes beyond and deeper the quanti + quali debate.
In his view, the categories that supposedly would differentiate quanti x quali approaches are collapsing. For example, (i) qualitative data is many times, quantified; (ii) large qualitative studies can allow for generalization (while scale/generalization would be a characteristic of quantitative studies), and (iii) induction and deduction inferences are almost always present.
In light of that, what are “mixed methods” ??
What “mixed methods” means is combining approaches that can bring robustness to your design, different perspectives/angles to look at the same object. Based on the questions you want to answer/what you want to test, ‘mixed methods’ for impact assessment could mean combining two or more quantitative methods. Therefore, different qualitative methods could be used to improve the robustness of an evaluation/research – and this would also be called ‘mixed methods’.
And then - going a bit beyond that: couldn’t we consider the mix of “colonizers’ “ with “indigenous “ approaches also “mixed methods”?
RE: How are mixed methods used in programme evaluation?
Dear colleagues, and thank you Jean for provoking this.
Please bear with me while I bring a drop of academic content to the discussion, hoping we can expand it a bit.
What are mixed methods after all? I think the quanti x quali debate is quite reductionist; and honestly after all these decades I cannot believe we are still discussing if RCTs are the gold standard.
I would like to bring an approach that called my attention, which was presented by Professor Paul Shaffer from Trent University (Canada). His approach is focused mixed methods for impact assessment – but I understand it can be extrapolated to other types of studies – such as outcome assessment. What I like about his proposal is that it goes beyond and deeper the quanti + quali debate.
In his view, the categories that supposedly would differentiate quanti x quali approaches are collapsing. For example, (i) qualitative data is many times, quantified; (ii) large qualitative studies can allow for generalization (while scale/generalization would be a characteristic of quantitative studies), and (iii) induction and deduction inferences are almost always present.
In light of that, what are “mixed methods” ??
What “mixed methods” means is combining approaches that can bring robustness to your design, different perspectives/angles to look at the same object. Based on the questions you want to answer/what you want to test, ‘mixed methods’ for impact assessment could mean combining two or more quantitative methods. Therefore, different qualitative methods could be used to improve the robustness of an evaluation/research – and this would also be called ‘mixed methods’.
And then - going a bit beyond that: couldn’t we consider the mix of “colonizers’ “ with “indigenous “ approaches also “mixed methods”?
I hope this can contribute to the reflection.
Cheers
Emilia
Emilia Bretan
Evaluation Specialist
FAO Office of Evaluation (OED)